Outlier Analysis in Risk Models

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How would you perform outlier analysis- detection and treatment?

Asked in the Technical round stage. This was one of 15 questions in the single technical round for Credit Risk Analyst.

Define an outlier and distinguish data errors from legitimate extreme observations.
Explain detection methods for numeric risk variables and when you would use each.
Describe an investigation and treatment process, including winsorization, transformation, exclusion, and retention.
Explain how you would validate the treatment and assess its effect on downstream credit-risk metrics or models.
Identify documentation, governance, and monitoring requirements.